import numpy as np
import csv
from datetime import datetime
from time import strftime


'''
Global and Local Empirical Bayes Smoothers with Gamma Model
'''

def getCurTime():
    """
    get current time
    Return value of the date string format(%Y-%m-%d %H:%M:%S)
    """
    format='%Y-%m-%d %H:%M:%S'
    sdate = None
    cdate = datetime.now()
    try:
        sdate = cdate.strftime(format)
    except:
        raise ValueError
    return sdate

def build_data_list(inputCSV):
    sKey = []
    fn = inputCSV
    ra = csv.DictReader(file(fn), dialect="excel")
    
    for record in ra:
        #print record[ra.fieldnames[0]], type(record[ra.fieldnames[-1]])
        for item in ra.fieldnames:
            temp = float(record[item])
            sKey.append(temp)
    sKey = np.array(sKey)
    sKey.shape=(-1,len(ra.fieldnames))
    return sKey



#--------------------------------------------------------------------------
#MAIN

if __name__ == "__main__":
    print '===================================================='
    print "begin at " + getCurTime()
    filepath = 'C:/_DATA/migration89_08/COUNTY Migration/clean/test/min_pop_500thousand/random_LGLR.csv'
    data = build_data_list(filepath)

    list = []
    output = []
    for i in range(0, len(data[0,:])):
        list = data[:,i]
        list = np.sort(list)
        output.append(list[4])
    print output

    #np.savetxt(filepath[:-4] + '_id.csv', output, delimiter=',', fmt = '%i')
